Research work (NIR)
A review of the state of the field, formulating hypotheses, testing them on your data. The result is a well-founded answer: whether the problem can be solved, and at what cost.
R&D · Research · Development
Research and development (R&D) in software and artificial intelligence
Classic R&D in Russia means instruments, microwave engineering and design documentation. We do R&D where the subject of research is an algorithm, a model or an architecture: when a solution does not exist yet and has to be obtained.
For companies that need a result that is not on the market: their own algorithm, a model for their own task, a test of a technical hypothesis before investing in a product.
What is included
Experimental development (OKR)
From a confirmed hypothesis to a working prototype: architecture, implementation, testing, documentation.
Our own models and libraries
Developing algorithms and models for the task when ready-made solutions do not fit on accuracy, licensing or perimeter requirements.
Specification and reporting
The technical specification, the test programme and methodology, stage reports. Documents that pass acceptance and are needed to account for the work.
Technology transfer
The result stays with you: source code, documentation, team training. We do not build dependence on ourselves.
How we work
Framing
We turn a vague goal into a testable hypothesis with a success criterion. Without that, R&D turns into infinity.
Research
A review of the field, experiments, early verification. We take on the risk of a negative result and report it at once.
Prototype
Implementing the solution and testing it to an agreed methodology.
Documents and handover
Stage reports, source code, training for your team.
Why us
A scientific base, not a declaration
We have our own research projects and open publications. Research competence is confirmed by artefacts, not by words in a presentation.
A negative result is also a result
We report early when a hypothesis has not been confirmed. That is cheaper than finding out after the project is delivered.
From paper to production
We do not stop at a prototype in a notebook: we take it to a working service if that is what you need.
Cases
Manufacturing · Building materials
MVP in operationPanel specs from CAD drawings in seconds, not hours
Reads DWG/DXF layouts and builds the Excel spec: 10–30 seconds instead of 2–15 hours by hand. All 784 panels of one real project matched the manual spec line by line.
- 784/784 and 189/189
- panels on one project and wall panels on another matched the manual specs line by line, size groups included; area within 0.001 m²
- 2–15 h → 10–30 s
- to produce a project spec: manual work vs app processing, measured on real projects
Real estate · PropTech marketplace
MVP in operationLand-plot marketplace with a next-step plan: MVP in 2 months
From a mock-up to a working platform: plot → works → contractor → request. Rule-based next-step engine, three dashboards, personal-data compliance. MVP in 2 months.
- 2 months
- from approved spec to pre-release MVP on an HTTPS stand — week 9 against the plan's own 10–13 week estimate
- 7 days
- from spec to the first full-implementation commit: 168 files, 21.5k lines, then two months of hardening to pre-release
Marketplace e-commerce · Pricing
PilotRepricing without manual price control: a contract-guaranteed pilot
Competitor prices tracked per SKU on the marketplace, a price computed inside an agreed corridor, applied only after confirmation. Pilot: 10 SKUs, setup within 14 days.
- 10 SKUs · 2 scenarios
- pilot scope; the SKU cap and both scenarios are enforced in code and verified by contract tests — the cap cannot be exceeded
- up to 14 days
- contractual setup window from client inputs to launch, then a 1-month pilot; the service tracks the dates and closes access when the period ends
EdTech · HR-tech
MVP in operation (demo stand)From business canvas to a student-work marketplace demo in about six weeks
The client had a business model and no product. We built a student-task marketplace MVP where the server enforces legal and platform rules, and put a demo stand live.
- ~6 weeks
- from first commit to a deployed demo with all workspaces; 7 working days in commit history
- 3 checks
- run by the server before a contractor is assigned: data consent, self-employed status, mentor — each with a plain refusal
AI infrastructure / multi-agent systems R&D
Research projectA multi-agent environment where rules are code, not prompts
In four days we built and open-sourced (MIT) an agent environment where constraints are enforced in code: cryptography, Byzantine consensus, reproducible experiments.
- same hash
- a repeated run and a replay of the log give a byte-identical final event hash — anyone can repeat it from the MIT-licensed code
- 187 of 187
- engine tests green — master branch, commit 625b81d, as of 05.10.2026
EdTech / AI research
Research projectLong-term student memory: from hypothesis to a working service
A neuromorphic memory core and cognitive digital twins of students: 32 REST endpoints, 368 tests and Lean 4 proofs — built in a 10-day sprint.
- 10 days
- from first commit to a release with formal verification, measured by commit dates
- 368
- test functions across 37 files, counted from code
Scientific computing / R&D
Research projectFrom mathematical theory to a verified numerical library in 9 months
A compensated-computation library: precision loss is visible and auditable, properties machine-proved in Lean 4, every numeric claim backed by a reproducible benchmark.
- 1.0 instead of 0.0
- residual preserved on the [1e16, 1, −1e16] aggregation that float silently drops; reproducible benchmark artifact in the repository
- ≥10x
- stability ratio vs float64 on catastrophic cancellation; pinned baseline under regression control in CI
Frequently asked questions
What is the difference between research (NIR) and development (OKR)?
Research (NIR) answers the question “is this possible, and under what conditions” — its result may be negative, and that is a normal outcome. Development (OKR) takes a possibility confirmed by the research and brings it to a design or a working sample.
Is there such a thing as R&D in software?
Yes. R&D is defined not by the industry but by the nature of the work: the presence of scientific or technical uncertainty that cannot be removed by standard design. Developing a new algorithm or model for a task that has no ready solution meets this criterion.
What if the result turns out negative?
That is a regular outcome of research, and it has value too: you get a well-founded answer that the path does not lead to the goal before you have invested in developing a product. We design the stages so that such an answer arrives as early and as cheaply as possible.
Who owns the results?
The rights to the result are set by the contract, and by default we assume they belong to the client. The specific terms on exclusive rights are fixed before work starts.
Related services
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